Create and utilize MySQL indexes
Creation and use of MySQL index
MySQL is a commonly used relational database management system used to store and manage data. Indexes are key to improving query performance when dealing with large amounts of data. This article will introduce how to create and use MySQL indexes and provide specific code examples.
1. What is an index?
An index is a data structure used to speed up the search for data in the database. It is similar to the table of contents of a book and can quickly locate the required data. The index in MySQL is implemented based on the B-tree data structure, and B-Tree indexes are usually used to improve query efficiency.
2. Why do you need an index?
In the absence of an index, the database needs to scan the entire table to find the required data, so the time complexity of the query will increase linearly as the amount of data increases. With the index, the database can directly locate the location containing the required data, greatly improving the efficiency of the query.
3. How to create an index?
- Specify the index when creating the table
When creating the table, you can specify the index by adding keywords after the column definition. For example, create a table named users
, which contains three columns: id
, name
, and age
, and is id# The sample code for creating an index on the ## and
name columns is as follows:
CREATE TABLE users ( id INT PRIMARY KEY, name VARCHAR(50), age INT, INDEX idx_id (id), INDEX idx_name (name) );
INDEX idx_id (id) is expressed as the
id column Create an index,
INDEX idx_name (name) means creating an index for the
name column. An index can be created for a specified column by using the
INDEX keyword after the column definition.
- Modify the table structure and add indexes
age column of the existing
users table is as follows:
ALTER TABLE users ADD INDEX idx_age (age);
ALTER TABLE is used For modifying the table structure,
ADD INDEX means adding an index,
idx_age is the name of the index, and
age is the column on which the index is to be created.
SELECT statement. For example, the sample code to query users who are 18 years or older in the
users table is as follows:
SELECT * FROM users WHERE age >= 18;
WHERE is used to specify the query conditions,
age >= 18 means to filter out users who are 18 years or older. MySQL will use indexes to quickly locate data that meets conditions.
- Thin Index
- Use index coverage query
- Pay attention to the order of index columns
- Avoid calculation or conversion of index columns
- MySQL official documentation: https://dev.mysql.com/doc/
- Network information: https://www.runoob.com/mysql/mysql-index.html
The above is the detailed content of Create and utilize MySQL indexes. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics

Common situations: 1. Use functions or operations; 2. Implicit type conversion; 3. Use not equal to (!= or <>); 4. Use the LIKE operator and start with a wildcard; 5. OR conditions; 6. NULL Value; 7. Low index selectivity; 8. Leftmost prefix principle of composite index; 9. Optimizer decision; 10. FORCE INDEX and IGNORE INDEX.

Full table scanning may be faster in MySQL than using indexes. Specific cases include: 1) the data volume is small; 2) when the query returns a large amount of data; 3) when the index column is not highly selective; 4) when the complex query. By analyzing query plans, optimizing indexes, avoiding over-index and regularly maintaining tables, you can make the best choices in practical applications.

MySQL indexes will fail when querying without using index columns, mismatching data types, improper use of prefix indexes, using functions or expressions for querying, incorrect order of index columns, frequent data updates, and too many or too few indexes. . 1. Do not use index columns for queries. In order to avoid this situation, you should use appropriate index columns in the query; 2. Data types do not match. When designing the table structure, you should ensure that the index columns match the data types of the query; 3. , Improper use of prefix index, you can use prefix index.

MySQL index leftmost principle principle and code examples In MySQL, indexing is one of the important means to improve query efficiency. Among them, the index leftmost principle is an important principle that we need to follow when using indexes to optimize queries. This article will introduce the principle of the leftmost principle of MySQL index and give some specific code examples. 1. The principle of index leftmost principle The index leftmost principle means that in an index, if the query condition is composed of multiple columns, then only the leftmost column in the index can be queried to fully satisfy the query conditions.

MySQL indexes are divided into the following types: 1. Ordinary index: matches value, range or prefix; 2. Unique index: ensures that the value is unique; 3. Primary key index: unique index of the primary key column; 4. Foreign key index: points to the primary key of another table ; 5. Full-text index: full-text search; 6. Hash index: equal match search; 7. Spatial index: geospatial search; 8. Composite index: search based on multiple columns.

MySQL supports four index types: B-Tree, Hash, Full-text, and Spatial. 1.B-Tree index is suitable for equal value search, range query and sorting. 2. Hash index is suitable for equal value searches, but does not support range query and sorting. 3. Full-text index is used for full-text search and is suitable for processing large amounts of text data. 4. Spatial index is used for geospatial data query and is suitable for GIS applications.

How to use MySQL indexes rationally and optimize database performance? Design protocols that technical students need to know! Introduction: In today's Internet era, the amount of data continues to grow, and database performance optimization has become a very important topic. As one of the most popular relational databases, MySQL’s rational use of indexes is crucial to improving database performance. This article will introduce how to use MySQL indexes rationally, optimize database performance, and provide some design rules for technical students. 1. Why use indexes? An index is a data structure that uses

Performance optimization strategies for data update and index maintenance of PHP and MySQL indexes and their impact on performance Summary: In the development of PHP and MySQL, indexes are an important tool for optimizing database query performance. This article will introduce the basic principles and usage of indexes, and explore the performance impact of indexes on data update and maintenance. At the same time, this article also provides some performance optimization strategies and specific code examples to help developers better understand and apply indexes. Basic principles and usage of indexes In MySQL, an index is a special number
